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application! The position Linköping University has a new cybersecurity lab that includes both a computer room for students and a server environment that can be used to simulate different scenarios related
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applications for a Doctoral student position in applied mathematics and machine learning for urban 3D reconstruction, within the Digital Twin Cities Centre (DTCC). The project aims to create analysis‑ready
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. The main research problems include mathematical theory, algorithms, and machine learning (deep learning) for inverse problems in artificial intelligence, as well as application to medical problems. About the
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, tightly collaborating research groups conducting research and education in Robotics and AI, Intelligent Autonomous Systems, Robot Learning, Machine Learning, Human-Robot Interaction and Natural
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management, information security management systems, etc.), or networking and infrastructure (e.g., computer networking, operating systems, system administration, cloud computing, etc.). You are expected
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at Sahlgrenska Academy of relevance include genomics, metagenomics, culturomics, proteomics, transcriptomics, software development, machine learning, and other statistical analyses of large-scale health data
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context. Ability to teach courses on adjacent programmes in the department, e.g. cybersecurity, human-computer interaction, embedded systems, etc. Experience in research in other areas currently being
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equations, Bayesian inference, large-scale computational methods, bioinformatics, data science, machine learning, optimisation, numerical methods. Please read more about the position and our department on our
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the opportunity for three weeks of training in higher education teaching and learning. The purpose of the position is to develop the independence as a researcher and to create the opportunity of further development
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-Physical Systems, you will teach at undergraduate and postgraduate level, including courses in computer architecture, embedded software, real-time systems, and AI-based perception for cyber-physical